How to model honeybee population dynamics: stage structure and seasonality

Western honeybees (Apis Mellifera) serve extremely important roles in our ecosystem and economics as they are responsible for pollinating $ 215 billion dollars annually over the world. Unfortunately, honeybee population and their colonies have been declined dramatically. The purpose of this article is to explore how we should model honeybee population with age structure and validate the model using empirical data so that we can identify different factors that lead to the survival and healthy of the honeybee colony. Our theoretical study combined with simulations and data validation suggests that the proper age structure incorporated in the model and seasonality are important for modeling honeybee population. Specifically, our work implies that the model assuming that (1) the adult bees are survived from the egg population rather than the brood population; and (2) seasonality in the queen egg laying rate, give the better fit than other honeybee models. The related theoretical and numerical analysis of the most fit model indicate that (a) the survival of honeybee colonies requires a large queen egg-laying rate and smaller values of the other life history parameter values in addition to proper initial condition; (b) both brood and adult bee populations are increasing with respect to the increase in the egg-laying rate and the decreasing in other parameter values; and (c) seasonality may promote/suppress the survival of the honeybee colony.

Backpack-mounted satellite transmitters do not affect reproductive performance in a migratory bustard

Backpack-mounted satellite transmitters (PTTs) are used extensively in the study of avian habitat use and of the movements and demography of medium- to large-bodied species, but can affect individuals’ performance and fitness. Transparent assessment of potential transmitter effects is important for both ethical accountability and confidence in, or adjustment to, life history parameter estimates. We assessed the influence of transmitters on seven reproductive parameters in Asian houbara Chlamydotis macqueenii, comparing 114 nests of 38 females carrying PTTs to 184 nests of untagged birds (non-PTT) over seven breeding seasons (2012–2018) in Uzbekistan. There was no evidence of any influence of PTTs on: lay date (non-PTT x̅ = 91.7 Julian day ± 12.3 SD; PTT x̅ = 95.1 Julian day ± 15.7 SD); clutch size (non-PTT x̅= 3.30 ± 0.68 SD; PTT x̅ = 3.25 ± 0.65 SD); mean egg weight at laying (non-PTT x̅ = 66.1 g ± 5.4 SD; PTT x̅ = 66.4 g ± 5.4 SD); nest success (non-PTT x̅ = 57.08% ± 4.3 SE; PTT x̅ = 58.24% ± 4.5 SE for nests started 2 April); egg hatchability (non-PTT x̅ = 88.3% ± 2.2 SE; PTT x̅ = 88.3% ± 2.6 SE); or chick survival to fledging from broods that had at least one surviving chick (non-PTT x̅ = 63.4% ± 4.2 SE; PTT x̅ = 64.4% ± 4.7 SE). High nesting propensity (97.3% year−1 ± 1.9% SE) of tagged birds indicated minimal PTT effect on breeding probability. These findings show that harness-mounted transmitters can give unbiased measures of demographic parameters of this species, and are relevant to other large-bodied, cursorial, ground-nesting birds of open habitats, particularly other bustards.

Intraspecific demography of the silky shark (Carcharhinus falciformis): implications for fisheries management

The silky shark (Carcharhinus falciformis) is one of the most heavily fished tropical shark species globally, and currently there is increasing concern for its conservation status. However, large differences and ambiguity in life history parameter estimates among regions complicates its conservation and fisheries management. Using a Leslie matrix model that incorporated stochastic effects, we analysed the intraspecific demography of C. falciformis using available life history data from seven regions. Among regions, large differences were observed in generation time and age-specific reproductive contributions. Carcharhinus falciformis generally had low resilience to fishing mortality (F) throughout its distribution. Age-at-first-capture and age-at-last-capture management approaches resulted in substantial differences among regions. This was largely influenced by age-at-maturity. However, in scrutinizing some regional life history studies, it is likely that sampling design and methodological differences among regions have resulted in inaccuracies in life history parameter estimates and subsequent demographic attributes. This implies that age and life-stage-dependent management approaches using these possibly inaccurate life history parameters may be inappropriate. We suggest that a greater emphasis needs to be placed on eliminating human sources of error in elasmobranch life history studies to ensure management for wide-ranging species, such as C. falciformis, is most effective.

Ensemble models for data-poor assessment: accounting for uncertainty in life-history information

Length measurements from fishery catch can be used in data-limited assessments to estimate important population parameters to guide management, but results are highly sensitive to assumptions about biological information. Ideally, local life history studies inform biological parameters. In the absence of reliable local estimates, scientists and managers face the difficult task of agreeing on fixed values for life-history parameters, often leading to additional uncertainty unquantified in the assessment or indecision defaulting to status-quo management. We propose an ensemble approach for incorporating life history uncertainty into data-limited stock assessments. We develop multivariate distributions of growth, mortality, and maturity parameter values, then use bivariate interpolation and stacking as an ensemble learning algorithm to propagate uncertainty into length-based, data-limited stock assessment models. Simulation testing demonstrated that stacking across life history parameter values leads to improved interval coverage over simple model averaging or assuming the parameter distribution means when the true life-history parameter values are unknown. We then applied the stacking approach for a U.S. Caribbean stock where the Scientific and Statistical Committee did not accept the assessment due to uncertainty in life history parameters. Stacking can better characterize uncertainty in stock status whenever life-history parameters are unknown but likely parameter distributions are available.

Brain evolution: A matter of constraints and permissions?

The article of Finlay et al. is an excellent example of identifying constraints in the development of the brain, and their implications on brain architecture in evolution. Here we further illustrate the importance of constraints by presenting a few examples of how a small number of biophysical mechanisms or even a single life history parameter can have an enormous impact on brain evolution.